April 3, 2024 — A new non-invasive technique for evaluating chickpea water efficiency, developed by researchers at the Hebrew University of Jerusalem, offers farmers a powerful tool to fine-tune irrigation and potentially elevate the sustainability of chickpea cultivation.

The new study published in Precision Agriculture has the potential to transform chickpea management, amplifying both crop yields and water efficiency. Chickpeas, also known as garbanzo beans, are an important global grain legume and are a staple protein source around the world, especially in the Middle East, South Asia, and the Mediterranean. The proposed method holds transformative potential for agriculture by enabling farmers to optimize irrigation schedules efficiently. This could lead to increased crop yields and improved water use efficiency, contributing to resource conservation and reduced environmental impact. Furthermore, the innovation has broader implications for global food security, showcasing the impact of advanced precision-smart agricultural technologies on sustainable farming practices.

Dual-field of view system for spectral data collection operated by Roy. Credit: Asaf Avneri

The remote sensing aspect of the project was led by researchers at the Hebrew University Robert H. Smith Institute of Plant Sciences and Genetics in Agriculture including Dr. Ittai Herrmann and Ph.D. candidate Roy Sadeh. They trained and tested spectral models for quick and non-invasive assessment of chickpea water status based on leaf water potential estimation from space and the ground. The agronomical aspects of the study were conducted by Hebrew University Prof. Shahal Abbo and Ph.D. student Asaf Avneri under the guidance of Dr. Ran Lati and Dr. David Bonfil at the Agricultural Research Organization in Israel.

The study consisted of two farm experiments and two commercial fields, using ground-based hyperspectral imaging and satellite images from the Vegetation and Environment monitoring on a New Micro-Satellite (VENmS) program. It aimed to remotely measure the leaf water potential of field-grown chickpeas under different irrigation treatments. While doing so, the limited effect of leaf area index on the ability to remotely estimate leaf water potential was revealed.

Additionally, this tool holds promise for physiologists and breeders in screening for drought-tolerant chickpea genotypes, paving the way for sustainable farming practices on a larger scale. The next step of the project is combining space-borne spectral data to improve leaf water potential estimation is ongoing.